Self‐harm, in‐person bullying and cyberbullying in secondary school‐aged children: A data linkage study in Wales

Abstract

Introduction: Although the evidence base on bullying victimization and self-harm in young people has been growing, most studies were cross-sectional, relied on self-reported non-validated measures of self-harm, and did not separate effects of in-person and cyberbullying. This study aimed to assess associations of self-harm following in-person bullying at school and cyberbullying victimization controlling for covariates. Methods: School survey data from 11 to 16 years pupils collected in 2017 from 39 Welsh secondary schools were linked to routinely collected data. Inverse probability weighting was performed to circumvent selection bias. Survival analyses for recurrent events were conducted to evaluate relative risks (adjusted hazard ratios [AHR]) of selfharm among bullying groups within 2 years following survey completion. Results: A total of 35.0% (weighted N = 6813) of pupils reported being bullied, with 18.1%, 6.4% and 10.5% being victims of in-person bullying at school only, cyberbullying only and both in-person bullying at school and cyberbullying respectively. Adjusting for covariates, effect sizes for self-harm were significant after being in-person bullied at school only (AHR = 2.2 [1.1-4.3]) and being both in-person bullied at school and cyberbullied (AHR = 2.2 [1.0-4.7]) but not being cyberbullied only (AHR = 1.2 [0.4-3.3]). Feeling lonely during recent summer holidays was also a robust predictor (AHR = 2.2 [1.2-4.0]). Conclusions: We reaffirm the role of in-person bullying victimization on self-harm. Pupils were twice as likely to self-harm following in-person bullying as their nonvictimised peers. Interventions for young people that minimize the potential impacts of bullying on self-harm should also include strategies to prevent loneliness.

Discovering the impact of bullying on adolescents through bibliometric analysis

“…From the network visualisation, it was identified that there were 198 items divided into 9 clusters with a number of links 6,205 with a total link strength of 35,460. After identifying the clusters, the impact of bullying on adolescent were suicidal behaviour, 12 mental disorder, 13 NSSI, 14 loneliness, 15 psychological distress 16 and ACEs. 17 From overlay visualisation, it was indicated that the newest topics that were widely researched related to the impact of bullying on adolescents were social anxiety, 18 suicidal ideation, 19 depressive symptoms, 20 suicidal thoughts, 21 integrated behaviour change (IBC) 22 and peer victimisation.…”

“…Loneliness causes someone who experiences it to feel empty, alone and unwanted even though the person is actually not alone and is in a busy environment. 15 This feeling of loneliness can occur in teenagers who experience bullying or are victims of bullying and teenagers who carry out bullying or are perpetrators of bullying.…”

“…58 Adolescents who have high levels of support from their friends have lower levels of bullying and victimisation. 15 Xiong et al 59 explained that individuals who have protective and reciprocal friendships can reduce children's involvement in bullying. Quality friendships can reduce individual involvement in bullying victimisation, because through best friends aggressive attacks from bullies can be avoided.…”

Machine learning in mental health and its relationship with epidemiological practice

“…There is no easy fix for these problems, and, compared to most other medical specialties, mental health researchers, especially those applying ML, often need to: (1) focus more resources on their data curation strategy; (2) address bias in their data with statistical tools such as inverse probability weighing, which can be applied to both epidemiology ( 33 ) and ML ( 34 ) methods; and (3) have a stronger patient and public involvement and engagement plan ( 35 ).…”

Cyberbullying and Non-Suicidal Self-Injury (NSSI) in Adolescence: Exploring Moderators and Mediators through a Systematic Review

“…Full-text assessment resulted in the exclusion of 27 studies that did not comply with the predetermined inclusion criteria, as outlined in the methodology section. Seventeen studies were excluded from analysis due to the outcome variable not aligning with the established criteria (e.g., unspecified lack of suicidal intent) [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. Four additional studies [62][63][64][65] were excluded because cyberbullying was not measured independently from other types of bullying or mistreatment.…”